The work investigates the development of an active smart rotor concept from an aero-servo-elastic perspective. An active smart rotor is a wind turbine rotor that, through a combination of sensors, control units and actuators, is able to alleviate the fluctuating part of the aerodynamic loads it has to withstand. The investigation focuses on a specific actuator type: the Adaptive Trailing Edge Flap (ATEF), which introduces a continuous deformation of the aft part of the airfoil camber-line.An aerodynamic model that accounts for the steady and unsteady effects of the flap deflection on a 2D airfoil section is developed, and, considering both attached and separated flow conditions, is validated by comparison against Computational Fluid Dynamic solutions and a panel code method. The aerodynamic model is integrated in the BEM-based aeroelastic simulation code HAWC2, thus providing a tool able to simulate the response of a wind turbine equipped with ATEF.A load analysis of the NREL 5 MW reference turbine in its baseline configuration reveals that the highest contribution to the blade flapwise fatigue damage originates from normal operation above rated wind speed, and from loads characterized by frequencies below 1 Hz. The analysis also reports that periodic load variations on the turbine blade account for nearly 11 % of the blade flapwise lifetime fatigue damage, while the rest is ascribed to load variations from disturbances of stochastic nature.The study proposes a smart rotor configuration with flaps laid out on the outer 20 % of the blade span, from 77 % to 97% of the blade length. The configuration is first tested with a simplified cyclic control approach, which gives a preliminary indication of the load alleviation potential, and also reveals the possibility to enhance the rotor energy capture below rated conditions by using the flaps.Two model based control algorithms are developed to actively alleviate the fatigue loads on the smart rotor with ATEF. The first algorithm features a linear quadratic regulator with periodic disturbance rejection, and controls the deflection of the flap on each blade based on measurements of the root flapwise bending moment; each blade is considered as an independent Single Input-Single Output system. The second algorithm is a Multiple Input-Multiple Output Model Predictive Control (MIMO-MPC), which monitors the whole turbine response, and controls all the available actuators: ATEF, individual blade pitch, and generator. Both algorithms include frequency-dependent weighting of the control actions in order to limit high frequency control activity, and thus effectively reduce actuators use and wear.The smart rotor performances are evaluated from HAWC2 simulations reproducing the response to standard turbulent wind fields. Both algorithms reduce the lifetime fatigue damage on the blade root flapwise bending moment by 15 % using the ATEF actuators. Whereas, by combining pitch and flap actions, the MIMO-MPC reports alleviation results close to 30 %. The MIMO-MPC requires lower flap activity, and also achieves higher reductions of the tower fatigue loads, thus indicating that a combined control approach that coordinates and integrates all available sensors and actuators has the potential for overall better results than achieved by a series of independent control systems.